A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generat...A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.展开更多
During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algor...During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algorithm for subimages, a large accumulated error will be made. In this paper, a relaxation algorithm of piecing-error for subimages is presented. It can eliminate the accumulated error in the traditional algorithm and greatly improve the quality of pieced image. Based on an initial pieced image, one can continuously adjust the center of every sub-image and its angle to lessen the error between the adjacent sub-images, so the quality of pieced image can be improved. The presented results indicate that the proposed algorithm can dramatically decrease the error while the quality of ultimate pieced image is still acceptable. The time complexity of this algorithm is O(n lnn).展开更多
基金Supported by the National Natural Science Foundation of China (Nos. 40771176, 40721001)
文摘A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.
文摘During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algorithm for subimages, a large accumulated error will be made. In this paper, a relaxation algorithm of piecing-error for subimages is presented. It can eliminate the accumulated error in the traditional algorithm and greatly improve the quality of pieced image. Based on an initial pieced image, one can continuously adjust the center of every sub-image and its angle to lessen the error between the adjacent sub-images, so the quality of pieced image can be improved. The presented results indicate that the proposed algorithm can dramatically decrease the error while the quality of ultimate pieced image is still acceptable. The time complexity of this algorithm is O(n lnn).
